Data-analysis with R, fall 2010
The last session of the fourth exercise group is shifted one week earlier. i.e. instead of the 16th of Dec, it is going to be held on 9th of Dec. The place and beginning hour is unaltered though.
This course is applicable to all levels, from basic to advanced studies. In the degree requirements of statistics this is a basic level course (one of the optionally compulsory data-analysis courses) and thus tailored for basic level statistics background.
This course provides an introduction to data-analysis based on the open source R environment and language, which is a globally adopted tool for exploratory statistics and modeling. R is both a programming
language developed for mathematical and statistical applications, as well as a extendable program for numerical computation. The large number of available extension libraries makes R an attractive choice for a wide range of application areas. During the course the participants will explore different kinds of datasets using both graphical and numerical approaches.
Mon 16-18 ,Thu 8-10, in lecture hall CK112
Slides of the course
2nd set of exercises
3rd set of exercises
Note that there is 17 problems in total (in three sets) that for passing the course one should effectively do at least 12 of them i.e. as ready as to present them in the demonstration sessions. It is also possible to send the solutions to the assistant by email for those who can not attend the demo sessions; The solution should be e-mailed no later than first session that those exercises are going to be presented i.e. Tue, 10 a.m. of every odd week. Also notice that solutions will not be posted online.
NOTE: Due to larg number of students, it is vital that students follow a uniform format if they opt to send their solutions via e-mail.
The files should be in pdf format with all the results and codes included. The name of the file should be of the form "lastname_fisrtname_set_C.pdf" that set can be either 1, 2, 3 corresponding to the exercises week and C is a vector showing the exercises in that set that you have solved.
One example is lastname_firstname_2_(1,2,5,6).pdf that means only first, second, fifth, and sixth exercises in the second set is presented in the file.
Student's solutions will be checked randomly and in case of fraud report the penalty is failing the course.
N.B. Those sent their solutions already, need not to resend them in case of not receiving any notice as a reply to their email.
There is no exam for this course. This pass/fail course credit can be obtained by solving at least 70% of exercises.
John Maindonald and John Braun, "Data Analysis and Graphics Using R - An Example-Based Approach",2003,Cambridge University Press
Did you forget to register? What to do.
Exercise group 1
weeks 45, 47, 49
Exercise group 2
weeks 45, 47, 49
Exercise group 3
weeks 46, 48, 50
Exercise group 4
weeks 46, 48, 49